A tweet is considered important when it receives many positive reactions from other accounts. The reactions may be in the form of likes or retweets. Retweets act as a form of endorsement, allowing Twitter users to forward the content generated by other users, thus raising the content's visibility. Hence it is a way of promoting a topic and is associated with the reputation of the user [1]}. Since retweeting is linked with popular topics and directly affects the reputation of a user, it is a key parameter for identifying possible fake account holders. As described in [2]}, bots or fake accounts depend more on retweeting existing content rather than posting new tweets. In our model, we consider the number of retweets as one of the main parameters for assigning an influence score to user accounts. To do so, we calculate the number of times a tweet is retweeted. Additionally, we calculate the total number of tweets for each user. The total number of tweets of user \(u_i\)  is denoted by \(N_{T}(u_i)\) . Finally, we calculate the retweet ratio (using Twitter grader) for each tweet by considering a tweet that is retweeted divided by the total number of tweets, given in equation (REF ).
\(R_{R}(u_i)=\frac{Retweets\ }{N_{T}(u_i)}\) 
